Position Detection for Electric Vehicle Dwcs Using Vi-Slam Method

Jun Cheng, Liyan Zhang, Qihong Chen, Rong Long
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Abstract

The dynamic wireless charging system (DWCS) is developed to solve the problems of large battery volume and mileage anxiety of electric vehicles. However, the accurate position detection for electric vehicle DWCS is facing challenge. The traditional communication, detection and estimation methods are difficult to accurately obtain the position. To tackle this problem, the visual inertial simultaneous localization and mapping (VI-SLAM) method is applied to the electric vehicles DWCS. Firstly, the graph optimization based tight coupling method is used to integrate the monocular visual and IMU measurements. Secondly, the NVIDIA TX2 and MYNT VI-sensor suite are assembled, which the MTi300-IMU is treated as the ground truth system. Finally, the mobile vehicle is controlled to race on the simulated DWCS pathway. The experimental result shows that the method achieves great performance with the accuracy of centimeter level. In particular, the root mean square error (RMSE) in X, Y, Z directions are 0.086,0.092,0.102, respectively.
基于Vi-Slam方法的电动汽车Dwcs位置检测
动态无线充电系统(DWCS)是为了解决电动汽车电池体积大、行驶里程焦虑等问题而开发的。然而,电动汽车DWCS的精确位置检测面临着挑战。传统的通信、检测和估计方法难以准确获取目标位置。为了解决这一问题,将视觉惯性同步定位与映射(VI-SLAM)方法应用到电动汽车DWCS中。首先,采用基于图优化的紧密耦合方法对单目视觉和IMU测量结果进行整合;其次,组装NVIDIA TX2和MYNT vi传感器套件,其中MTi300-IMU作为地面真相系统。最后,控制移动车辆在模拟的DWCS路径上进行比赛。实验结果表明,该方法取得了较好的效果,精度达到厘米级。其中,X、Y、Z方向的均方根误差(RMSE)分别为0.086、0.092、0.102。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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